Methods for quantifying driving performance errors associated with sleep onset are of key importance for reducing the number of sleep related crashes. In the US, driver sleepiness is a major cause of motor vehicle crashes and is responsible for approximately 40,000 injuries and 1500 deaths each year. In one study, 55% of 1000 drivers surveyed indicated that they had driven while drowsy and 23% had fallen asleep at the wheel. This confirms other studies that sleepiness or sleep onset may play a role in vehicle crashes that are erroneously attributed to other causes.
Microsleep events are a useful indicator of sleep onset. A microsleep event often occurs as a result of sleep deprivation, or mental fatigue, sleep apnea, narcolepsy, or hypersomnia.
There are standardized methods for monitoring microsleep, which include: monitoring the electroencephalogram (EEG) and electrooculogram (EOG), video, test of performance, and the like. Of all these methods, the EEG is considered the most reliable for measuring sleepiness. However, both EEG and EOG, require the use of electrodes, which are attached to the subject, thereby making these methods inappropriate to routinely monitor any operators conducting fatigue prone tasks, such as, for example, vehicle drivers. The other methods are impractical because they are both difficult to set-up and because they require intensive data analysis by humans thereby making data treatment difficult to automate.
There are various ways by which microsleep episodes can be identified. Some experts define microsleep according to behavioral criteria (eyelids closure), while others rely on electroencephalogram markers such as a 3-15 second episode (shorter durations would be difficult to visually detect and longer times would qualify as sleep onset.) during which 4-7 Hz (theta wave) activity replaced the waking 14-20 Hz (alpha wave) background rhythm.
Microsleep, subjectively related to the sensation of “nodding off”, is associated with the interruption of the blinking artifacts characteristic of full wakefulness. During microsleep events, attention lapses can impair the ability to detect and respond to crucial stimuli and events. For example, microsleeps (or microsleep episodes) can become extremely dangerous when occurring during situations which require continual alertness, such as driving a motor vehicle or operating machinery. People who experience microsleeps usually remain unaware of them, instead believing themselves to have been awake the whole time, or feeling a sensation of ‘spacing out’. The sleepy driver is at very high risk of having an accident during a microsleep episode. Many accidents have occurred because of microsleep episodes.
Clearly, the ability to detect microsleep events would be useful as a means of alerting and warning drowsy drivers of such events.
Several studies have used “quantitative” EEG methods to identify driver sleepiness. Theta power (EEG waves), and the frequency of theta bursts typically increase during prolonged driving, and are associated with poor driving performance. Disadvantageously, these techniques typically average EEG activity over several seconds (up to 1 minute), and therefore could not be used to detect brief microsleep events of between 3 seconds and 15 seconds.
A variety of physiological measures have been proposed to alert drivers to the onset of drowsiness.
One of the most investigated is PERCLOS (or PERcent CLOSure), which measures drowsiness as the percent of time a driver's eyes are closed over a time period. When a sufficient number of open/closed patterns are obtained, PERCLOS will trigger an alarm. PERCLOS works at percentages greater than 80%, which typically means that within 1 minute, the eyes of the individual must be closed for 48 seconds before an alarm is triggered. Clearly, this delay in unacceptable in tasks such as driving a vehicle because by the time PERCLOS activates the alarm, the driver will already have either fallen asleep, or be on the verge of falling asleep. Therefore, disadvantageously PERCLOS is too slow a system to allow preventive actions to be taken before an individual, such as a driver, experiences the first signs of sleepiness.
EOG records, which are made to exclude potential artifacts during EEG records, also show that normal eye blinks often continue during microsleep events, indicating that the eyes are at least partially open.
Another physiological measure, which is based on measurements of eye closure and which supposedly alerts drivers to the onset of drowsiness, is the measurement of peak blink velocities, as described in U.S. Pat. No. 7,071,831B2. The system described therein includes a pair of glasses or spectacle frames that must be worn by the individuals in order to monitor the occurrence of eye blinks. However, this kind of device must be carried or worn by operators (i.e. portable devices).
Thus, there is a need for a detection method and device for the detection of microsleep events in a subject as an indicator of sleep onset that is able to detect brief microsleep events, at early stages, not requiring the use of electrodes or other portable devices.